"brand", "mentions", "coverage"?
monitor_brand
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Communication & knowledgePublic skills
Public Relations
Brand monitoring and PR operations for AI agents — media sentiment, crisis detection, share of voice, press releases, and social listening via GDELT and Reddit.
What this skill teaches
A reusable playbook for a specific kind of work.
An MCP server tells an agent which actions are available. A skill adds the judgment around those actions: how to recognize the job, which sequence to follow, what to avoid, and how to decide that the result is complete.
Orchestrate PR operations — monitor brand mentions, analyze media sentiment, detect crises early, compare share of voice, track coverage volume, format press releases, and monitor social discussions. Use when checking brand reputation, detecting PR crises, comparing media coverage, writing press releases, or…
Architecture
How Public Relations guides an ADK-Rust agent.
The skill stays readable and portable because it contains instructions rather than service credentials or business data. ADK-Rust supplies it to the agent, the agent chooses from its reviewed tool boundary, and the connected MCP server performs the authenticated operation.
01
User request
The agent receives a goal expressed in ordinary language.
02
Public Relations skill
Matches intent, supplies the decision guide, and narrows the tool boundary.
03
ADK-Rust agent
Plans the workflow and streams each meaningful step through the runtime.
04
mcp-pr
Executes authenticated operations against the system that owns the capability.
05
Verified result
The skill's completion rules shape the evidence returned to the user.
Decision guide
How the agent turns a request into the right action.
These routes come directly from the skill instructions. They help the model recognize intent and select a focused tool or workflow instead of improvising across the entire capability surface.
"sentiment", "positive", "negative"?
analyze_sentiment
"crisis", "bad press", "negative spike"?
detect_crisis
"share of voice", "vs competitor"?
compare_share_of_voice
"volume", "how much coverage"?
track_coverage_volume
"press release", "announcement"?
format_press_release
"reddit", "social", "discussions"?
monitor_reddit
"background", "about company"?
get_entity_background
Proven workflows
Repeatable sequences for useful outcomes.
A workflow joins several tool calls into a task the user actually recognizes. The skill explains the sequence and the intended result while ADK-Rust streams the agent's progress through the shared runtime.
012-3 calls
Brand Health
Mentions + sentiment + crisis check
021 calls
Crisis Detection
Early warning on negative spikes
031 calls
Press Release
Wire-service formatted announcement
041 calls
Competitive
Share of voice comparison
051 calls
Social Listening
Reddit discussion monitoring
Tool boundary
The skill may use 8 documented tools.
This allowlist is declared by the skill. It keeps the agent focused on the actions needed for this job while mcp-pr retains responsibility for authentication, validation, and the connected system.
monitor_brand
analyze_sentiment
track_coverage_volume
compare_share_of_voice
detect_crisis
get_entity_background
monitor_reddit
format_press_release
Working rules
What the agent should do.
- Check detect_crisis daily for early warning
- Include sentiment context with all coverage reports
- Compare share of voice against competitors quarterly
Operating boundaries
What the agent should avoid.
- Don't ignore negative sentiment spikes (escalate immediately)
- Don't publish press releases without review
Install and connect
Add the skill beside the capability it expects.
Install the repository where your ADK-Rust skill loader can discover it, connect mcp-pr, and confirm the declared tools are available before asking the agent to use the workflow.
Install the skill
git clone https://github.com/zavora-ai/skill-public-relations.git ~/.skills/skills/public-relationsADK-Rust loading shape
let skills = SkillLoader::from_dir("~/.skills/skills").await?;
let skill = skills.load("public-relations").await?;
let agent = LlmAgentBuilder::new("agent")
.instruction(skill.instructions())
.tools(skill.allowed_tools(toolset)?)
.build()?;The repository's compatibility statement: Requires mcp-pr server connected (GDELT, Wikipedia, Reddit — free, zero config).
Official documentation
Read the complete skill package.
The repository remains authoritative for its exact instructions, examples, helper scripts, assets, MCP requirements, license, and later updates.
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Source record
Repository metadata for this skill entry.
- License
- Apache-2.0
- Allowed tools
- 8
- References
- 3
- Revision
- c553b125f434
- Updated
- May 31, 2026